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Exploring Hybrid: A (hybrid) SIG to discuss hybrid conferences

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 27 Apr 2022 Italy Publisher:ACMJournal:CHI Conference on Human Factors in Computing Systems Extended Abstracts

Authors: SIGCHI Executive Committee; Adriana S Vivacqua; Andrew L Kun; Cale Passmore; Helena Mentis; Josh Andres; Kashyap Todi; +13 Authors

doi: 10.1145/3491101.3516405

handle: 11583/2961690

Exploring Hybrid: A (hybrid) SIG to discuss hybrid conferences

- Summary
- Subjects
- Metrics

Abstract

In this special interest group (SIG), we follow up on previous conversations around hybrid models for conferences, conducted in open sessions by the ACM Special Interest Group on Computer-Human Interaction (SIGCHI) Executive Committee (EC). The COVID-19 pandemic led to a sudden shift to virtual conferences; as we start to go back to in-person events, it is important to reflect on the types of events we desire, and design these accordingly. With this SIG, we hope to share experiences from previous conferences (successful or not) and discuss potential solutions to pending issues. This SIG will be led by VP at Large Adriana S. Vivacqua, with the participation of other EC members.

Country

Italy

Related Organizations

University of Maryland, College Park
United States
Georgia Institute of Technology
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University of California System
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Pennsylvania State University
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Polytechnic University of Turin
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Keywords

hybrid; conferences; sustainability; design

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	3
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average